[00:00:02] Angeline Gavino:
Data driven decisions are the best decisions that you can make. If you always have data to back you up, you know that one way or another, you're going in the right direction.
[00:00:12] Adil Saleh:
Welcome to the Hyperengage Podcast. We are so happy to have you along our journey. Here, we uncover bits of knowledge from some of the greatest minds in tech. We unearth the hows, whys, and whats that drive the tech of today. Welcome to the movement.
[00:00:30] Adil Saleh:
Hey, greetings everybody. This is Adil from Hyperengage Podcast. I have tatered, my co host, and Angeline from Catalon. Thank you very much, Angeline, for taking the time. Absolutely. Thanks for having me. It's really great to be here. Absolutely, likewise. So just for our audience. Angelina she's a VP of customer success and support at Catalog. It is a repulsed platform for quality management, quality insurance for technical teams from testing to deploying. It's a big use case. We'll explore more about Catalog after we explore a bit about Angeline.
[00:01:06] Adil Saleh:
So, Angelina, starting up, I've seen you've been working with different startups at different levels of different sizes of tech businesses in the past ten years. You've taken on roles more in the support size. In a nutshell, it's more in the customer facing. So how did you see yourself transitioning over these years with startups to mid sized businesses and now also small size businesses like Catalog? So how was your journey panning out to be where you are today? Right, good question. So my professional career spans a period of 15 plus years now, nine years of which are in leadership roles. And for the past six years, I've primarily been working with startups. And it was a very bold move after working for the same company, a publicly listed company, for close to a decade, around nine years prior. And I realized that I actually love working at startups. I love the fast paced environment. I love how you see your impact. There's no small or big, you see what you're working and the output that you're working on. And personally, I've actually moved from client facing roles to non client facing roles and back. I started, as you rightly said, a deal in support organization, and then I moved into an operations role, and then I move into a client facing role again, and then I move up, move horizontally, vertically across the organizations, too. So it's really only through having this variety of experience also experiencing both sides, right? The operational side and the client facing side, that I realized that I enjoy working directly with customers. I like being able to build relationships, helping customers succeed. And there's something fulfilling about being able to help your customers and solve their problems. And personally, I love how conversations from one client to another can be vastly different. So it keeps me on my toes and keeps my day to day exciting as well. And I think what I really love is that client facing roles or customer success. In general, customer support, customer experience is industry agnostic. So I've moved from different industries myself. I don't think I've been in a single industry from one company to the next. So I think that's what I love, that I'm able to transfer my knowledge and the skills that I've built from company to company just because you have that foundational skills that you need to succeed. Being in a client facing role, in a nutshell, that's been kind of like the experience for the past 15 years or so. That's amazing.
[00:04:02] Adil Saleh:
Before we dive into Catalan, I'm really interested because you had operational background and you also had customer facing background. So can you tell us a little bit maybe of how integrating those experiences actually helps you become a better VP and because you've had almost a comprehensive look at the process from a whole from a different lens?
[00:04:24] Angeline Gavino:
Absolutely. I think you put it right, you get a holistic view of how the business runs, not just the client facing side of things, but how it runs in the background as well. And I think a lot of the things that I learned in Auckman, my operations role, I bring that hat into my current role today, being in charge of customer success and customer support. So, for example, I'm super data driven. I actually love data. I love digging into data, working on Excel sheets, things like that. And even until now, I like drilling down and looking at that kind of information because I realized early on in my career that data driven decisions are the best decisions that you can make. If you always have data to back you up, you know that one way or another, you're going in the right direction. So I think that's one of the things that I learned early on in my career, I apply until now. So that's actually a lot of the key focus that I have for this year is surrounding data, how we're looking at data, and how we're empowering my teams to make decisions and service their customers using data. I think you see the difficulty of both sides of the business, right. Client facing role. Yeah, people think it's easy, like just talking to customers and things like that, building relationships, fine, but you know, there's a lot of struggles as well into that. And on the flip side of things, being able to support those clients facing teams, because that's exactly what the operations team does. Right. They're in the back end, but they're helping or empowering the teams that are on the front end to really do what they do well. So I think it helps me give that holistic view of the business as well and to understand the difficulties of the teams, but also the clients. Absolutely. So you're pretty like a dance, like you are partnering up with your customers. You're bridging the gaps, you're crossing bridges at times when there are challenges at any stage of the customer journey.
So now talking about Carolone, looking at it as a solution, it's big enough a problem like we are in the startup community, like Hybrid Engagers, as we all know, it's a support hub for startups. So we'll talk about we'll start with startups. So for a startup to ship features that they need to ship it in quick succession, it's more of an Iterative cycle as it is for a smaller mid sized business. So in the first one and a half, two years, they try to do the right things, they try to ship fast, make sure the quality is top notch, they have the right systems, I'm sure they need to optimize the cost as well. That's another challenge. But how you're facilitating startups, I've seen some of your customers that are pretty much mid size, maybe SMB, but how you are trying to penetrate towards startups. So how a startup can perceive value and what kind of startups using Catalon that's true. So as you mentioned earlier, right, catalog is we're a series, a startup and we do provide that all in one solution or quality management platform. So we work, like you said, with companies who create products, web or mobile applications API and we help them automate their software testing. And typically what I've seen is that startups in the early phase of their maturity, they would do a lot of this manually. And I actually would say that it's more than just startups. Generally companies would start doing all of these in a manual way and you would see, I actually see that there's some parallelism between customer success, customer experience in general, like when they mature. So you do a lot of things very manually and then usually the first shift is when you want to scale and you move from manual to automating your testing. And that's where Catalon comes in. Typically, our customers are moving from that space into just automating, just starting to automate their testing processes and then also moving from there's a lot of open source free applications and platforms available out there. That does kind of what they're trying to do. Testing helps them test their applications before they really ship it to production or to their customers. But it lacks a lot of features and it requires really a lot of work to maintain it. And so the value proposition we offer to SMB in particular is to smoothen that transition from manual to automation at a very affordable cost. Because usually startup companies would have a very small development team, small testing team, and they don't have the budget to really spend on just like all of these automation tools available because this isn't the only tool in their tech stack, so to speak. So we help them make that transition. And one of the value proposition of Catalan as well is we are a low code application. So even if a tester has no developer background, has no coding background. They are able to start Catalon from the get go so they can kick start their testing even if they have very little background in that. Interesting. Very interesting. Especially this, I'm so glad that you mentioned this no code thing, low code thing, because a lot of these it is not easy for startup to hire a technical resource for quality assurance. Number one challenge, they're not going to get easily in some regions. Let's not talk about just the United States in South America it's not that easy. In some parts of Europe it's not easy. Central Asia. It's not easy. Second, they are not a touch way more expensive as compared to the known technical resources. But if someone with CS background, that's okay, but not a lot of experience. If they can use catalog as a local technology, easy to understand, easy to take action and test drive all those sprints that need to be shipped on a regular basis to make sure the end delivery is of quality and they're getting their customer satisfaction at that.
[00:10:30] Adil Saleh:
So now, talking about the post sales journey, how many team members you have alongside as a VT, just on the success side if you want to include support as a part of success because a lot of CS teams that do that just mentioned that. Otherwise, how big is the team, how you're segmenting customers across different regions and how those journeys are being mapped predominantly and how smartly you're basically adopting customers. How much of it is more digital CS or smart CS? As you mentioned that you are so into data and data centricity. So I would appreciate sure. I have to do the math and some counting because we do service a big customer base and a global customer base at that. So within the Customer Success organization, basically those responsible for the post sales customer journey, there's around 16, including the leaders, the regional leaders, and I do have around ten in the support organization. So focusing a little bit on how we structure a Customer success team. Our Customer Success team is responsible for renewal and expansion. So we do hold like revenue numbers. We are directly responsible. It's not just about providing Csqls. We're really directly responsible and accountable for ensuring customers renew and that we're expanding our customer base as well through Upsells, crosssells and such. We structure our team in a way that allows us to service the global customer base. So there is a regional would say assignment, if you may, or allocation. So there's somebody responsible for Americas, for APAC and EMEA and we also do segment our portfolio so that the CSMS are either handling enterprise or commercial. And commercial being a mix of mid market and SMB customers. And we have a small, very small team that we're still developing of the digital Customer Success Managers. That is, we're starting to build this automation automating basically the whole customer lifecycle journey in tandem and in support of what the name CSMS are doing. So we're not putting digital success or CS as primarily targeted towards, let's say, SMB or subset of our clients. The goal of digital CS is to automate the whole customer journey for all our customers, enterprise or commercial. And one key change that we did this year was to create an onboarding manager role because we don't have an implementation team. Our product is, I wouldn't say plug and play, but it's very easy to get going, so you don't need like, a long implementation process. However, last year, looking at what happened last year, we realized that there's a lot we can do to improve the onboarding process. And so we created a dedicated onboarding manager role as well, who is in charge of the high touch onboarding of our enterprise and commercial segment. So that's kind of how we are structuring the team today. So that's great.
[00:14:04] Angeline Gavino:
So you want to ask something better?
[00:14:06] Adil Saleh:
Yeah, I'm super curious. You said, Angeline, you're really data driven. So with this team and being so global, how do you empower your CS team to also be data driven just like you? Because like you said, at the end of the day, when you have data to back you up, that's when you're actually able to drive the most effective outcomes that show some metrics, like, okay, we're going in the right direction here. So can you talk a little bit about how you enable and empower the CS team to be data driven and what that looks like? Maybe?
[00:14:41] Angeline Gavino:
Sure. And this is something I'm very passionate about because due to just my background in general, and this year, actually, since beginning of this year, this has been a key focus because last year we've been focusing on kind of standardizing operations or setting the processes in place, like the foundational processes that will allow us to scale. We're still at an early stage startup, a series, a startup. So there's a lot of things that we're making sure we get the processes and the technology that we're using right that will allow us to scale for growth later. And this year, there's a lot of focus for me and for the team around making sure that we're bringing data to the team. And we started some sort of account health score system last year, but we realized it wasn't very effective and it wasn't giving us the right signals. And so this year it's a matter of let's put data in front of our CSMS that will allow them to just take action. So we do have an internal, how should I call it, internal data team that helps us with creating dashboards for us, making sure that we have all the data we need, product, telemetry, financial data, like, kind of combining all of those to give us a holistic view. That's actually one of my main projects for this year. So we're at the stage where we're pulling all of those data together and putting it in a dashboard, kind of like a command center for our account manager CSMS as well, and making sure that it's data driven. And we're kind of doing a spin off of account health score. We don't do red, amber, green signals. How I do it, how we're trying to do it today is let's understand churn risk and let's understand expansion opportunity, because as a CSM, before becoming a leader, I struggle with the green amber, red signals, like, yes, green. What does it mean? They're happy? Does it mean that there's an expansion opportunity? It doesn't really give me much information, especially because our CS is very, as I mentioned, revenue generating team. And so we kind of structure it like, super straightforward. These are your accounts at churn risk because of these particular reasons. Some signals usually around product adoption, product usage that we're using as signals to identify churn risk. And then there's also the expansion potentials, also more or less based on product usage, those that have propensity to potentially expand because they're doing these things, they're exhibiting these behaviors. We want to display that to the CSMS. And the reason why we want to do this is because the color coded signals like, what do I do next here? They know this is return risk. You need to say this account, this is a expansion potential. Go reach out. Understand if there really is an expansion potential now, we're not there yet. We're in that early stages where we're kind of formulating all of this. I think what makes us different a little bit is we actually don't use a customer success platform today. One of my mistakes in my previous startups was setting up a customer success platform before we got my team and the processes in place. And I didn't want to make the same mistake again. Like, starting with technology first before you look at the people, and you got. To make sure that you have all the change management that it requires before introducing any kind of these platforms.
[00:18:38] Angeline Gavino:
So you mentioned about the product usage. I'm sure you have customer success managers. They have like, multiple accounts that they're looking after. Their book of business, on my assumption, would be around 20, 25, 30, maybe 50, depending upon some of the strategic accounts that you have that you guys are serving. So talking on a CSM level, I'm just thinking as a CSM, how you guys basically centralize all the product usage metrics to your CSMS so that they make decisions and they indicate risk, because a lot of these adoption and retention, it's driven by how you are staying on top of the product usage, customer patterns, their attributes. So what kind of technology or maybe system that you have in place right now for your CSMS? If I'm a CSM looking after 35 accounts, how am I going to be staying on top on everyday, weekly, monthly basis? That this usage pattern is getting on the lower side. I need to make sure I get into touch or maybe to send in some training document. How is that is more systematic? I'm sure everybody does it. There is no way that we can get rid of it. But how you are trying to in place systems. As a startup, as a growing startup, you'll be surprised that we didn't have any of these last year. We're kind of running blind. We have a CRM where we understand customer sentiment because we do customer satisfaction surveys, things like that. But product telemetry was very hard for us to see as a whole. We do have some system in place. We have a back end system that allows us to check data, but we have to do it manually, one by one for each of our accounts. So like you said, if a CSM has 20 or more accounts, that means they're checking those probably on a regular basis just to make sure that they're not missing anything. So that was a difficulty because we didn't have the right systems in place. And so this year we are taking it in a phased approach. So the first part of this quarter was around just getting data visibility. We started getting dashboards in place where they can see how many users are logging in for like, let's say a particular period of time, or how many of the accounts have no logins or no activity for the past year. Because typically non usage, I think this is universal, non usage is a sign of potential churn. Right. We started with just getting the visibility first and we recognized that the challenge there is that anyone could interpret the data differently depending on how senior you are in the team. Because we do have different CSMS with different backgrounds. Some of them have been so used to having data and so it was very hard for them, like transitioning into a startup where we were and they had to understand, okay, where do I get the data? That was super important for us. But then there's also others that interpret the data differently. So in a nutshell, not everyone is seeing the data differently. And so the next step of this whole data project that we're having right now is how do we make it so that they don't have to decipher data, they don't have to do some data analysis we just put in front of them. These are the accounts that you have to take action on based on train risk and expansion potential, which was what I was discussing earlier. We're going to create this dashboard, kind of like a command center of sorts. And every day they go in there first thing in the morning and they see, okay, these are my churn accounts, churn risk accounts, these are my expansion potential accounts. And just take action instead of trying to decipher the data. Now the next part of that is how do we automate? Because right now what's going to happen is they're going to read that, okay, these are my counsel churn risk, I'm going to have to call them up, I'm going to reach out, understand what's going on, or same thing on the expansion potential. And for me, the next step is we empower the teams to do more and we're going to try to automate a lot of these repetitive actions. Right? That's part of our digital CS plans, say non usage. There's potentially an automated email that comes up to understand, hey, anyway, this is something that a CSM would do themselves, but they're just going to do it manually. Now, why not just automate it? Because it is something they will do most likely every day on a regular basis. And then the next next phase, and I don't know if that's something that we can do this year is how do we use AI and machine learning to enable the team to get us all of this. Because right now, the churn risk that I'm talking about and the expansion potential, these are all still based on assumption, based on our observation of how our customers behave in the past hypothesis. Yes. Right? This is like how we do account health scores via the customer success platforms. I don't know. Actually, I made a LinkedIn post about this, like, I think late last year. AI is so prevalent in other industries, why haven't I seen AI and customer success? There is generative. Is that how you call it? AI. Now that I'm seeing generative, AI driven insights, AI driven risk, just AI machine learning, looking at our data and helping us understand what are the behaviors that pinpoints to a potential churn or pinpoints to a potential expansion. So it's kind of like the last phase. It's a bit ambitious. I've actually spoke with a few companies, startup companies that are starting to do this, like creating this kind of platform. So it's still exciting. There's a lot of things that we have to do, basically, but we got to walk before we can run.
[00:24:26] Adil Saleh:
First, you're taking that data centricity and you're getting everything together in one, like you said, command center, in a sense. And then almost adding a layer of then once you have this command center and your team is able to go to it, then how do you take action on it? Because just like you said, some interpretations are different depending on your experience or what conversations you have. And the interpretation is kind of wide open. So how do you think initially because you're going to launch the command center and all this data centricity, you're going to launch it before the AI is able to come in and maybe provide those actionable insights without someone needing to think about it. So how are you going to combat maybe this interpretation that is left open?
[00:25:11] Angeline Gavino:
We're trying to do, and this is something that we're doing as a team, we're going to have to come up with a list of best practices based on the signals that we have. So we're saying that this is the churn risk because, for example, they gave a negative CSAT score, a very bad CSAT score, for example. And what is the approach to that? Kind of. So we're going to gather a list of best practices, of action, of actions that we feel should be taken based on the signals that we're going to see in the command center, in the dashboard, and continue to iterate and validate that as we go along. Because as I mentioned, the drawback of this is these are all theories, assumptions based on obviously data back. They stole data back based on back with our experience as well. But we have to constantly, number one, actually validate the signals too, just like how we would do with the normal health score. The churn rates that we showed you, were they really churn risk or maybe they're not. And then when we do this, are they more responsive versus when we do this so it doesn't stop like with that. So we really do have to continuously review, reiter iterate and just understand if it's giving us valid signals and we're going on the right track, basically, yeah. It's very important to evolve over time and learning the patterns and behaviors and it is not possible for the entire segment, like entire installed base of your product. But of course, you can segregate, you can segment the customer journeys and then you can automate those journeys over time. And these CS platforms and a lot of startups, they are investing into the post sales and they are trying to first enable startups like yours to stay on top of product usage because a lot of success is driven by how customers using and leveraging and utilizing the product they bought. So how that product is delivering value over time. So that is where I think this is just a suggestion like yourself. While you're building segmenting these customers and automating these journeys, you focus on the product activities, how you can automate that person and your customer facing team, be it support or success or sales, is taking decisions based on the product attributes and the customer behaviors and patterns.
[00:27:40] Adil Saleh: Love the conversation, by the way. You've been so much explanatory and you've been very much expressive, genuinely expressive about an opinion about what you want to do as a VP. So thank you very much for your time today. It was really nice conversation. Absolutely. Thank you so much. It was an interesting conversation for me. I love digging into just data and also just kind of having a soundboard like you guys just validating a lot of the things that I'm doing right now. I think it's really good.
[00:28:13] Angeline Gavino:: Thank you so much for your time. Both.
[00:28:17] Taylor: Before we wrap up, I think it's a super important point. Angeline that you're putting that focus on the data driven aspect of things because it's not driven by opinion. Of course, right now, as you migrate into being more data driven, there is some opinions in there and it's not completely data driven, but to have the backbone that you're having some kind of metrics to back up whatever you're thinking, like, is the call the right approach? Or maybe it's an email, or maybe you have to sit down with them and you seeing all that and having metrics actually analyze that. We definitely believe that's the way of the future for CS. Every other niche within a company is data driven between sales and marketing. So. Why not? CS?
Angleine: Absolutely. So that's how AI is going to come into play when you learn the patterns, when you're so definitive fishing about the patterns, you give prompts to AI and that's how you train your AI model. Just like Chad GPT, you give him the prompts, make him understand the patterns, and then they give results. So it's similar to that down the road. Once you know all the patterns, all these journeys, that's how you can embed AI generative like Model inside. Just like HubSpot has done for their customers, salesforce is doing for their customers, drama Lee is doing it. I mean, it's going to be a new norm. Every technology company is trying to do something AI augmented or AI powered. Yeah, I do realize it's still very nascent in the customer success space, but there are more and more players that are coming out that are incorporating AI ML in the tools that they're providing. So really excited to see as well how that will pan out. That's a very big topic, by the way, and I'm sure you have so much to offer. So that's why we're trying to be a support hub for startups and we are grouping these startups together in a slack community. Very soon you'll have an email where you'll find a lot of IC startups, tech startups, some CS leaders that you can take advice from, take their time, discuss your problems and maybe see how they are doing at scale. So that's what we're trying to accomplish with this network and this entire Hyper India channel. So I'm sure you'll have so much to offer for other startups, just like you have all of these experiences, diverse experiences. Amazing what you guys are doing as well.
[00:30:35] Angeline Gavino:
Thank you so much.
[00:30:36] Adil Saleh:
Have a good rest of your day.
[00:30:37] Angeline Gavino:
We'll have to connect sometime in six months to twelve months to see how all this processes panned out.
[00:30:43] Adil Saleh:
Yeah, absolutely love to see myself as well and look back and see how far we've come along, but yeah, have a beautiful day. That's true.
[00:30:55] Adil Saleh:
All right, bye. Thank you so very much for staying with us on the episode. Please hear your feedback at adil@hyperengage,io. We definitely need it. We will see you next time with another guest. On the stage with some concrete tips on how to operate better as a customer success leader and how you can empower engagements with building some meaningful relationships. We qualify people for the episode just to make sure we bring the value to the listeners. Do reach us out if you want to refer any CS leader. Until next time, goodbye and have a good rest of your day.
